I am looking for materials or someone that are working on the development of hybrid algorithm, especially in the field of Multi-objective clustering optimization algorithms.
Multi-objective clustering optimization algorithms have been developed in data mining and machine learning. Popular ones include NSGA-II, MOEA/D, MSR, MOPSO, and NSGA-III. These algorithms optimize multi-objective problems by incorporating clustering objectives, decomposing problems into single-objective subproblems, applying simulated annealing, and improving convergence and diversity.
Hello, this is not what you exactly want, but we applied multiobjective triclustering formulation here (in terms of several quality measures, one can take Pareto-optimal "winners"):
Article Triadic Formal Concept Analysis and triclustering: searching...